Wireless communications systems are widely deployed to provide various types of communication such as voice, packet data, and so on. These systems may be based on code division multiple access (CDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), or other multiple access techniques to allow multiple devices to share a common communications medium. Such systems can conform to standards such as Third-Generation Partnership Project 2 (3gpp2, or “cdma2000”), Third-Generation Partnership (3gpp, or “W-CDMA”), or Long Term Evolution (“LTE” or “LTE-A”).
In such communications systems, it is oftentimes desired to estimate the frequency response of a communications channel (i.e., the “channel response”) for use in equalization schemes to combat channel distortion at the receiver. Prior art techniques for estimating the channel response include extracting a pilot portion of a received signal having known frequency and content sent by the transmitter, and reconstructing the channel response by using the pilot tones to weight a set of discrete Fourier (harmonic) basis functions (i.e., discrete Fourier transform or DFT-based channel estimation). In practice, there may be an error floor when using DFT-based channel estimation due to the truncation of Fourier basis functions. An alternative technique is to apply a minimum mean square error (MMSE) criterion to estimate the coefficients of the channel response. However, such an approach may require continuous estimation of the signal-to-noise ratio (SNR) of the channel, which may be challenging when only a limited number of pilot observations is available.
It would be desirable to provide efficient and novel techniques for estimating the response of a communications channel.